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fastTS  

Fast Time Series Modeling for Seasonal Series with Exogenous Variables
View on CRAN: Click here


Download and install fastTS package within the R console
Install from CRAN:
install.packages("fastTS")

Install from Github:
library("remotes")
install_github("cran/fastTS")

Install by package version:
library("remotes")
install_version("fastTS", "1.0.1")



Attach the package and use:
library("fastTS")
Maintained by
Ryan Andrew Peterson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-02-07
Latest Update: 2024-02-07
Description:
An implementation of sparsity-ranked lasso and related methods for time series data. This methodology is especially useful for large time series with exogenous features and/or complex seasonality. Originally described in Peterson and Cavanaugh (2022) in the context of variable selection with interactions and/or polynomials, ranked sparsity is a philosophy with methods useful for variable selection in the presence of prior informational asymmetry. This situation exists for time series data with complex seasonality, as shown in Peterson and Cavanaugh (2024) , which also describes this package in greater detail. The sparsity-ranked penalization methods for time series implemented in 'fastTS' can fit large/complex/high-frequency time series quickly, even with a high-dimensional exogenous feature set. The method is considerably faster than its competitors, while often producing more accurate predictions. Also included is a long hourly series of arrivals into the University of Iowa Emergency Department with concurrent local temperature.
How to cite:
Ryan Andrew Peterson (2024). fastTS: Fast Time Series Modeling for Seasonal Series with Exogenous Variables. R package version 1.0.1, https://cran.r-project.org/web/packages/fastTS. Accessed 03 Dec. 2024.
Previous versions and publish date:
0.1.2 (2024-02-07 19:20), 1.0.0 (2024-03-07 19:00), 1.0.1 (2024-03-28 22:40)
Other packages that cited fastTS R package
View fastTS citation profile
Other R packages that fastTS depends, imports, suggests or enhances
Complete documentation for fastTS
Functions, R codes and Examples using the fastTS R package
Some associated functions: fastTS . internal . predict.fastTS . uihc_ed_arrivals . 
Some associated R codes: data.R . fastTS.R . helpers.R . prediction.R .  Full fastTS package functions and examples
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